Bibliographic record
Abstract
Some interracial couples continue to report experiencing family opposition and having limited access to family support. With the dramatic rise in housing prices, young adults' ability to own a home increasingly depends on access to financial assistance from parents. These two phenomena raise the question: do interracial couples systematically have lower homeownership rates than endogamous couples? As most couples hold their wealth in house equity, lower homeownership rates may limit wealth accumulation over the long run. We pool data from the 2007-2021 American Community Survey (ACS) and compare the homeownership rates of Millennials in intermarriages with those of their peers in ethno-racially endogamous marriages. The homeownership rates of interracial couples are "in-between" those of couples in endogamous unions belonging to the husband's or wife's ethno-racial groups. Intermarrying does not appear to systematically reduce interracial couples' ability to own a home by reducing family support. Instead, the rise in intermarriages is likely reducing the ethno-racial inequality in homeownership rates. Nonetheless, couples in marriages involving an ethno-racial minority spouse consistently have lower homeownership rates than endogamous White couples. The White/non-White divide in homeownership rates underscore the importance of implementing housing policy that enhances opportunities for homeownership among interracial and endogamous minority couples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".